One multiple access technique that is becoming increasingly popular in communication systems is code division multiple access (CDMA). In a direct sequence (DS) CDMA system, a plurality of substantially orthogonal codes (usually taking the form of pseudo-random noise sequences) are used to spread spectrum modulate user signals within the system. Each of the modulated user signals has an overlapping frequency spectrum with other modulated user signals in the system. However, because the underlying modulation codes are substantially orthogonal, each user signal can be independently demodulated by performing a correlation operation using the corresponding code.
For various reasons, the codes within the modulated user signals received in a CDMA-based receiver may not be fully orthogonal, thus resulting in interference between the different users. This interference is known as multiple access interference (MAI). In a conventional single-user CDMA detection strategy, the individual users are each separately detected without regard for interference from the other users. In a technique known as multi-user detection (MUD), on the other hand, information about multiple users is utilized jointly to better detect each individual user. MUD techniques can be implemented in connection with a wide variety of detector types including, for example, maximum-likelihood (ML) detectors, linear detectors, and subtractive interference cancellation detectors. One form of linear detector that shows promise for MUD implementation is the minimum mean-squared error (MMSE) detector. However, MMSE-based MUD detectors have traditionally been considered too complex for implementation within, for example, cellular-type communication systems. This complexity is in large part due to the multiplicity of users (and corresponding high dimensionality) that typically needs to be accounted for within such systems.